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Introduction:

Social Network Analysis (SNA) has become an increasingly popular tool for identifying influencers in various fields such as marketing, politics, and healthcare. The ability to map out and analyze the relationships between individuals and groups within a network has provided valuable insights into how information flows, decisions are made, and influence is exerted. In this thesis, we will explore the use of Social Network Analysis for Influencer Identification, with a focus on understanding the key factors that contribute to an individual’s influence within a network.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter 2: Literature Review
2.1 Introduction to Social Network Analysis
2.2 Theoretical Foundations of Influence
2.3 Methods for Identifying Influencers
2.4 Applications of SNA in Various Fields
2.5 Challenges and Criticisms of SNA
2.6 Existing Studies on Influencer Identification
2.7 Influence Metrics and Measurement
2.8 Relationship between Network Structure and Influence
2.9 Network Dynamics and Influence
2.10 Ethical Considerations in Influencer Identification

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection
3.3 Data Analysis
3.4 Sampling Techniques
3.5 Network Visualization
3.6 Software Tools for SNA
3.7 Case Study Selection
3.8 Ethical Considerations

Chapter 4: Discussion of Findings
4.1 Overview of Findings
4.2 Influencer Identification Framework
4.3 Case Study Analysis
4.4 Comparative Analysis of Different Networks
4.5 Implications for Practice
4.6 Recommendations for Future Research
4.7 Limitations of the Study
4.8 Contributions to the Field
4.9 Managerial and Policy Implications

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Implications for Theory and Practice
5.3 Contributions to the Field
5.4 Limitations of the Study
5.5 Future Research Directions
5.6 Conclusion

Thesis Overview:

Social Network Analysis (SNA) has emerged as a powerful tool for identifying influencers within networks. This thesis aims to explore the use of SNA for Influencer Identification, focusing on the key factors that contribute to an individual’s influence within a network.

Chapter 1 provides an introduction to the topic, including the background of the study, the problem statement, objectives, limitations, scope, significance, structure of the thesis, and definition of terms.

Chapter 2 conducts a comprehensive literature review on SNA, theoretical foundations of influence, methods for identifying influencers, applications of SNA in various fields, challenges, existing studies, metrics, measurement, network structure and dynamics, ethical considerations, and more.

Chapter 3 outlines the research methodology, including research design, data collection, analysis, sampling, visualization, software tools, case study selection, and ethical considerations.

Chapter 4 discusses the findings, including the development of an influencer identification framework, case study analysis, comparative analysis, implications for practice, recommendations, limitations, contributions, and managerial and policy implications.

Chapter 5 concludes with a summary of findings, implications, contributions, limitations, future research directions, and a final conclusion.

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